This work proposes a new method for using reduced-order models in lieu of high-fidelity analysis during the sensitivity analysis step. Reduced-order models are developed using a combination of proper orthogonal decomposition and radial basis functions. Interpolation using reduced-order models based on proper orthogonal decomposition is compared against normal optimization on a general airfoil shape optimization problem. The interpolation procedure does not require additional high-fidelity evaluations to construct new reduced-order models. The errors associated with the reduced-order models themselves as well as the gradients calculated from them are compared. The effects of each approach on the overall optimization paths, times, and function counts are also examined. Presented as Paper 2014-0111 at the 10th AIAA Multidisciplinary Design Optimization Conference, National Harbor, MD, 13-17 January 2014


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    Title :

    Reduced-Order Techniques for Sensitivity Analysis and Design Optimization of Aerospace Systems



    Published in:

    AIAA journal ; 53 , 12 ; 3567-3576


    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    50.93 / 55.50 Luftfahrzeugtechnik / 50.93 Weltraumforschung / 55.60 Raumfahrttechnik / 55.50 / 55.60
    Local classification TIB:    770/7040




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